Abstract: Radio frequency identification (RFID) applications have grown rapidly in many industries, especially in indoor location identification. The advantage of using received signal strength indicator (RSSI) values as an indoor location measurement method is a cost-effective approach without installing extra hardware. Because the accuracy of many positioning schemes using RSSI values is limited by interference factors and the environment, thus it is challenging to use RFID location techniques based on integrating positioning algorithm design. This study proposes the location estimation approach and analyzes a scheme relying on RSSI values to minimize location errors. In addition, this paper examines different factors that affect location accuracy by integrating the backpropagation neural network (BPN) with the LANDMARC algorithm in a training phase and an online phase. First, the training phase computes coordinates obtained from the LANDMARC algorithm, which uses RSSI values and the real coordinates of reference tags as training data for constructing an appropriate BPN architecture and training length. Second, in the online phase, the LANDMARC algorithm calculates the coordinates of tracking tags, which are then used as BPN inputs to obtain location estimates. The results show that the proposed scheme can estimate locations more accurately compared to LANDMARC without extra devices.
Abstract: It is suggested to evaluate environmental performance
of energy sector using Data Envelopment Analysis with nondiscretionary
factors (DEA-ND) with relative indicators as inputs and
outputs. The latter allows for comparison of the objects essentially
different in size. Inclusion of non-discretionary factors serves
separation of the indicators that are beyond the control of the objects.
A virtual perfect object comprised of maximal outputs and minimal
inputs was added to the group of actual ones. In this setting, explicit
solution of the DEA-ND problem was obtained. Energy sector of the
United States was analyzed using suggested approach for the period
of 1980 – 2006 with expected values of economic indicators for 2030
used for forming the perfect object. It was obtained that
environmental performance has been increasing steadily for the
period from 7.7% through 50.0% but still remains well below the
prospected level
Abstract: Soil erosion is the most serious problem faced at
global and local level. So planning of soil conservation measures has
become prominent agenda in the view of water basin managers. To
plan for the soil conservation measures, the information on soil
erosion is essential. Universal Soil Loss Equation (USLE), Revised
Universal Soil Loss Equation 1 (RUSLE1or RUSLE) and Modified
Universal Soil Loss Equation (MUSLE), RUSLE 1.06, RUSLE1.06c,
RUSLE2 are most widely used conventional erosion estimation
methods. The essential drawbacks of USLE, RUSLE1 equations are
that they are based on average annual values of its parameters and so
their applicability to small temporal scale is questionable. Also these
equations do not estimate runoff generated soil erosion. So
applicability of these equations to estimate runoff generated soil
erosion is questionable. Data used in formation of USLE, RUSLE1
equations was plot data so its applicability at greater spatial scale
needs some scale correction factors to be induced. On the other hand
MUSLE is unsuitable for predicting sediment yield of small and large
events. Although the new revised forms of USLE like RUSLE 1.06,
RUSLE1.06c and RUSLE2 were land use independent and they have
almost cleared all the drawbacks in earlier versions like USLE and
RUSLE1, they are based on the regional data of specific area and
their applicability to other areas having different climate, soil, land
use is questionable. These conventional equations are applicable for
sheet and rill erosion and unable to predict gully erosion and spatial
pattern of rills. So the research was focused on development of nonconventional
(other than conventional) methods of soil erosion
estimation. When these non-conventional methods are combined with
GIS and RS, gives spatial distribution of soil erosion. In the present
paper the review of literature on non- conventional methods of soil
erosion estimation supported by GIS and RS is presented.
Abstract: Analysis for the generalized thermoelastic Lamb
waves, which propagates in anisotropic thin plates in generalized
thermoelasticity, is presented employing normal mode expansion
method. The displacement and temperature fields are expressed by a
summation of the symmetric and antisymmetric thermoelastic modes
in the surface thermal stresses and thermal gradient free orthotropic
plate, therefore the theory is particularly appropriate for waveform
analyses of Lamb waves in thin anisotropic plates. The transient
waveforms excited by the thermoelastic expansion are analyzed for
an orthotropic thin plate. The obtained results show that the theory
provides a quantitative analysis to characterize anisotropic
thermoelastic stiffness properties of plates by wave detection. Finally
numerical calculations have been presented for a NaF crystal, and the
dispersion curves for the lowest modes of the symmetric and
antisymmetric vibrations are represented graphically at different
values of thermal relaxation time. However, the methods can be used
for other materials as well
Abstract: The progress of concentrations of particular heavy metals was assessed in chosen localities in region Moravia, the Czech Republic, from 2007 to 2009. Particular metals were observed in localities with various types and characterization of zone. Pb, Ni, As and Cd were emphasized as a result of their toxicity and potential adverse health effect to the exposed population. The progress of metal concentrations and their health effects in the most polluted localities were examined. According to the results, the air pollution limit values were not exceeded. Based on the health risk assessment, the probability of developing tumorous diseases is acceptable, except for the increased probability of cancer risk from long-term exposure to As.
Abstract: This study defines a methodology to compute unitary costs for freight transportation modes. The main objective was to gather relevant costs data to support the formulation and evaluation of railway, road, pipelines and port projects. This article will concentrate on the following steps: Compilation and analysis of relevant modal cost studies, Methodological adjustments to make cost figures comparable between studies, Definition of typology and scope of transportation modes, Analysis and validation of cost values for relevant freight transportation modes in Chile. In order to define the comparison methodology for the costs between the different transportation modes, it was necessary to consider that the relevant cost depends on who performs the comparison. Thus, for the transportation user (e.g. exporter) the pertinent costs are the mode tariffs, whereas from the operators perspective (e.g. rail manager), the pertinent costs are the operating costs of each mode.
Abstract: Multilevel inverters supplied from equal and constant
dc sources almost don-t exist in practical applications. The variation
of the dc sources affects the values of the switching angles required
for each specific harmonic profile, as well as increases the difficulty
of the harmonic elimination-s equations. This paper presents an
extremely fast optimal solution of harmonic elimination of multilevel
inverters with non-equal dc sources using Tanaka's fuzzy linear
regression formulation. A set of mathematical equations describing
the general output waveform of the multilevel inverter with nonequal
dc sources is formulated. Fuzzy linear regression is then
employed to compute the optimal solution set of switching angles.
Abstract: Hazardous Material transportation by road is coupled
with inherent risk of accidents causing loss of lives, grievous injuries,
property losses and environmental damages. The most common type
of hazmat road accident happens to be the releases (78%) of
hazardous substances, followed by fires (28%), explosions (14%) and
vapour/ gas clouds (6 %.).
The paper is discussing initially the probable 'Impact Zones'
likely to be caused by one flammable (LPG) and one toxic (ethylene
oxide) chemicals being transported through a sizable segment of a
State Highway connecting three notified Industrial zones in Surat
district in Western India housing 26 MAH industrial units. Three
'hotspots' were identified along the highway segment depending on
the particular chemical traffic and the population distribution within
500 meters on either sides. The thermal radiation and explosion
overpressure have been calculated for LPG / Ethylene Oxide BLEVE
scenarios along with toxic release scenario for ethylene oxide.
Besides, the dispersion calculations for ethylene oxide toxic release
have been made for each 'hotspot' location and the impact zones
have been mapped for the LOC concentrations. Subsequently, the
maximum Initial Isolation and the protective zones were calculated
based on ERPG-3 and ERPG-2 values of ethylene oxide respectively
which are estimated taking the worst case scenario under worst
weather conditions. The data analysis will be helpful to the local
administration in capacity building with respect to rescue /
evacuation and medical preparedness and quantitative inputs to
augment the District Offsite Emergency Plan document.
Abstract: Amount of dissolve oxygen in a river has a great direct affect on aquatic macroinvertebrates and this would influence on the region ecosystem indirectly. In this paper it is tried to predict dissolved oxygen in rivers by employing an easy Fuzzy Logic Modeling, Wang Mendel method. This model just uses previous records to estimate upcoming values. For this purpose daily and hourly records of eight stations in Au Sable watershed in Michigan, United States are employed for 12 years and 50 days period respectively. Calculations indicate that for long period prediction it is better to increase input intervals. But for filling missed data it is advisable to decrease the interval. Increasing partitioning of input and output features influence a little on accuracy but make the model too time consuming. Increment in number of input data also act like number of partitioning. Large amount of train data does not modify accuracy essentially, so, an optimum training length should be selected.
Abstract: Data Envelopment Analysis (DEA) is a methodology
that computes efficiency values for decision making units (DMU) in a
given period by comparing the outputs with the inputs. In many cases,
there are some time lag between the consumption of inputs and the
production of outputs. For a long-term research project, it is hard to
avoid the production lead time phenomenon. This time lag effect
should be considered in evaluating the performance of organizations.
This paper suggests a model to calculate efficiency values for the
performance evaluation problem with time lag. In the experimental
part, the proposed methods are compared with the CCR and an
existing time lag model using the data set of the 21st century frontier
R&D program which is a long-term national R&D program of Korea.
Abstract: The problem of estimating time-varying regression is
inevitably concerned with the necessity to choose the appropriate
level of model volatility - ranging from the full stationarity of instant
regression models to their absolute independence of each other. In the
stationary case the number of regression coefficients to be estimated
equals that of regressors, whereas the absence of any smoothness
assumptions augments the dimension of the unknown vector by the
factor of the time-series length. The Akaike Information Criterion
is a commonly adopted means of adjusting a model to the given
data set within a succession of nested parametric model classes,
but its crucial restriction is that the classes are rigidly defined by
the growing integer-valued dimension of the unknown vector. To
make the Kullback information maximization principle underlying the
classical AIC applicable to the problem of time-varying regression
estimation, we extend it onto a wider class of data models in which
the dimension of the parameter is fixed, but the freedom of its values
is softly constrained by a family of continuously nested a priori
probability distributions.
Abstract: To evaluate genetic variation of wheat (Triticum
aestivum) affected by heat and drought stress on eight Australian
wheat genotypes that are parents of Doubled Haploid (HD) mapping
populations at the vegetative stage, the water stress experiment was
conducted at 65% field capacity in growth room. Heat stress
experiment was conducted in the research field under irrigation over
summer. Result show that water stress decreased dry shoot weight
and RWC but increased osmolarity and means of Fv/Fm values in all
varieties except for Krichauff. Krichauff and Kukri had the
maximum RWC under drought stress. Trident variety was shown
maximum WUE, osmolarity (610 mM/Kg), dry mater, quantum yield
and Fv/Fm 0.815 under water stress condition. However, the
recovery of quantum yield was apparent between 4 to 7 days after
stress in all varieties. Nevertheless, increase in water stress after that
lead to strong decrease in quantum yield. There was a genetic
variation for leaf pigments content among varieties under heat stress.
Heat stress decreased significantly the total chlorophyll content that
measured by SPAD. Krichauff had maximum value of Anthocyanin
content (2.978 A/g FW), chlorophyll a+b (2.001 mg/g FW) and
chlorophyll a (1.502 mg/g FW). Maximum value of chlorophyll b
(0.515 mg/g FW) and Carotenoids (0.234 mg/g FW) content
belonged to Kukri. The quantum yield of all varieties decreased
significantly, when the weather temperature increased from 28 ÔùªC to
36 ÔùªC during the 6 days. However, the recovery of quantum yield
was apparent after 8th day in all varieties. The maximum decrease
and recovery in quantum yield was observed in Krichauff. Drought
and heat tolerant and moderately tolerant wheat genotypes were
included Trident, Krichauff, Kukri and RAC875. Molineux, Berkut
and Excalibur were clustered into most sensitive and moderately
sensitive genotypes. Finally, the results show that there was a
significantly genetic variation among the eight varieties that were
studied under heat and water stress.
Abstract: MC (Management Control)& IC (Internal Control) – what is the relationship? (an empirical study into the definitions between MC and IC) based on the wider considerations of Internal Control and Management Control terms, attention is focused not only on the financial aspects but also more on the soft aspects of the business, such as culture, behaviour, standards and values. The limited considerations of Management Control are focused mainly in the hard, financial aspects of business operation. The definitions of Management Control and Internal Control are often used interchangeably and the results of this empirical study reveal that Management Control is part of Internal Control, there is no causal link between the two concepts. Based on the interpretation of the respondents, the term Management Control has moved from a broad term to a more limited term with the soft aspects of the influencing of behaviour, performance measurements, incentives and culture. This paper is an exploratory study based on qualitative research and on a qualitative matrix method analysis of the thematic definition of the terms Management Control and Internal Control.
Abstract: In this study, the numerical solution of unsteady flow
between two concentric rotating spheres with suction and blowing at
their boundaries is presented. The spheres are rotating about a
common axis of rotation while their angular velocities are constant.
The Navier-Stokes equations are solved by employing the finite
difference method and implicit scheme. The resulting flow patterns
are presented for various values of the flow parameters including
rotational Reynolds number Re , and a blowing/suction Reynolds
number Rew . Viscous torques at the inner and the outer spheres are
calculated, too. It is seen that increasing the amount of suction and
blowing decrease the size of eddies generated in the annulus.
Abstract: Rural tourism has many economical, environmental, and socio-cultural benefits. However, the development of rural tourism compared to urban tourism is also faced with several challenges added to the disadvantages of rural tourism. The aim of this study is to design a model of the factors affecting the motivations of rural tourists, in an attempt to improve the understanding of rural tourism motivation for the development of that form of tourism. The proposed model is based on a sound theoretical framework. It was designed following a literature review of tourism motivation theoretical frameworks and of rural tourism motivation factors. The tourism motivation theoretical framework that fitted to the best all rural tourism motivation factors was then chosen as the basis for the proposed model. This study hence found that the push and pull tourism motivation framework and the inner and outer directed values theory are the most adequate theoretical frameworks for the modeling of rural tourism motivation.
Abstract: In this research, we propose to use the discrete cosine
transform to approximate the cumulative distributions of data cube
cells- values. The cosine transform is known to have a good energy
compaction property and thus can approximate data distribution
functions easily with small number of coefficients. The derived
estimator is accurate and easy to update. We perform experiments to
compare its performance with a well-known technique - the (Haar)
wavelet. The experimental results show that the cosine transform
performs much better than the wavelet in estimation accuracy, speed,
space efficiency, and update easiness.
Abstract: Web usage mining algorithms have been widely
utilized for modeling user web navigation behavior. In this study we
advance a model for mining of user-s navigation pattern. The model
makes user model based on expectation-maximization (EM)
algorithm.An EM algorithm is used in statistics for finding maximum
likelihood estimates of parameters in probabilistic models, where the
model depends on unobserved latent variables. The experimental
results represent that by decreasing the number of clusters, the log
likelihood converges toward lower values and probability of the
largest cluster will be decreased while the number of the clusters
increases in each treatment.
Abstract: In this work, we present a comparison between two
techniques of image compression. In the first case, the image is
divided in blocks which are collected according to zig-zag scan. In
the second one, we apply the Fast Cosine Transform to the image,
and then the transformed image is divided in blocks which are
collected according to zig-zag scan too. Later, in both cases, the
Karhunen-Loève transform is applied to mentioned blocks. On the
other hand, we present three new metrics based on eigenvalues for a
better comparative evaluation of the techniques. Simulations show
that the combined version is the best, with minor Mean Absolute
Error (MAE) and Mean Squared Error (MSE), higher Peak Signal to
Noise Ratio (PSNR) and better image quality. Finally, new technique
was far superior to JPEG and JPEG2000.
Abstract: Saturated hydraulic conductivity of Soil is an
important property in processes involving water and solute flow in
soils. Saturated hydraulic conductivity of soil is difficult to measure
and can be highly variable, requiring a large number of replicate
samples. In this study, 60 sets of soil samples were collected at
Saqhez region of Kurdistan province-IRAN. The statistics such as
Correlation Coefficient (R), Root Mean Square Error (RMSE), Mean
Bias Error (MBE) and Mean Absolute Error (MAE) were used to
evaluation the multiple linear regression models varied with number
of dataset. In this study the multiple linear regression models were
evaluated when only percentage of sand, silt, and clay content (SSC)
were used as inputs, and when SSC and bulk density, Bd, (SSC+Bd)
were used as inputs. The R, RMSE, MBE and MAE values of the 50
dataset for method (SSC), were calculated 0.925, 15.29, -1.03 and
12.51 and for method (SSC+Bd), were calculated 0.927, 15.28,-1.11
and 12.92, respectively, for relationship obtained from multiple
linear regressions on data. Also the R, RMSE, MBE and MAE values
of the 10 dataset for method (SSC), were calculated 0.725, 19.62, -
9.87 and 18.91 and for method (SSC+Bd), were calculated 0.618,
24.69, -17.37 and 22.16, respectively, which shows when number of
dataset increase, precision of estimated saturated hydraulic
conductivity, increases.
Abstract: Deprivation indices are widely used in public health
study. These indices are also referred as the index of inequalities or
disadvantage. Even though, there are many indices that have been
built before, it is believed to be less appropriate to use the existing
indices to be applied in other countries or areas which had different
socio-economic conditions and different geographical characteristics.
The objective of this study is to construct the index based on the
geographical and socio-economic factors in Peninsular Malaysia
which is defined as the weighted household-based deprivation index.
This study has employed the variables based on household items,
household facilities, school attendance and education level obtained
from Malaysia 2000 census report. The factor analysis is used to
extract the latent variables from indicators, or reducing the
observable variable into smaller amount of components or factor.
Based on the factor analysis, two extracted factors were selected,
known as Basic Household Amenities and Middle-Class Household
Item factor. It is observed that the district with a lower index values
are located in the less developed states like Kelantan, Terengganu
and Kedah. Meanwhile, the areas with high index values are located
in developed states such as Pulau Pinang, W.P. Kuala Lumpur and
Selangor.